textacy
NLP, before and after spaCy
Decision gist · record as of 2026-08-14
Yes, if you are already using spaCy and need pre- or post-processing utilities. The package fills a real gap with low install friction and no known vulnerabilities. However, dormant maintenance (last release 1230 days ago) means you should expect no active support or updates; use it for stable, well-defined tasks rather than as a foundation for new feature development.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a spaCy language model to be installed and loaded separately before textacy can process text.
- Low install friction with a pure-Python wheel.
- Maintenance is dormant—last release was 1230 days ago and the last commit was 2023-09-22—but the repository remains active and supports Python 3.9, 3.10, 3.11.
License · maintenance · safety
permissive license (permissive) — Licensed under Apache License 2.0 (permissive). You may use, modify, and distribute freely in commercial and private projects, provided you include the license notice.
last release 2023-04-02 (1230 days) · last repo commit 2023-09-22 · 2,240 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 102,787 downloads/mo, #12,847 on PyPI
Alternatives
Verify before relying
pip install textacy
import textacy
# Requires a spaCy model to be loaded separately
import spacy
nlp = spacy.load('en_core_web_sm')
doc = nlp('Your text here')
extracted = textacy.extract.ngrams(doc, n=2)- Specific spaCy version compatibility requirements beyond what the fact sheet states.
- Performance characteristics when processing large document collections.
- Whether all features remain functional given the dormant maintenance status.
What it is and what it does
textacy is a Python library that builds on spaCy to handle NLP tasks before and after core linguistic processing. It delegates tokenization, part-of-speech tagging, and dependency parsing to spaCy, then adds convenience methods for working with one or many documents, cleaning and normalizing raw text, extracting structured information (n-grams, entities, acronyms, keyterms, SVO triples), comparing strings using similarity metrics, training and visualizing topic models, and computing text readability and lexical diversity statistics.
The package depends on 14 runtime libraries including numpy, scipy, scikit-learn, networkx, and spacy. It is distributed as a pure-Python wheel with low install friction. The project is in Beta status and has been dormant since April 2023, though the repository remains public with occasional commits. It supports Python 3.9 and later.
Use it for
- Extract n-grams, entities, and keyterms from documents after spaCy processing.
- Clean and normalize raw text before feeding it into spaCy for linguistic analysis.
- Compute readability metrics and lexical diversity statistics on text corpora.
- Train and visualize topic models from document collections.
- Compare and rank strings using similarity metrics for deduplication or matching tasks.
- Load prepared datasets with text and metadata for rapid prototyping of NLP workflows.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are already using spaCy and need pre- or post-processing utilities.
The package fills a real gap with low install friction and no known vulnerabilities. However, dormant maintenance (last release 1230 days ago) means you should expect no active support or updates; use it for stable, well-defined tasks rather than as a foundation for new feature development.
Install
textacy on PyPI
Before you install
Low install friction with a pure-Python wheel. Maintenance is dormant—last release was 1230 days ago and the last commit was 2023-09-22—but the repository remains active and supports Python 3.9, 3.10, 3.11.
Requires a spaCy language model to be installed and loaded separately before textacy can process text.
License in practice
Licensed under Apache License 2.0 (permissive). You may use, modify, and distribute freely in commercial and private projects, provided you include the license notice.
Quickstart
pip install textacy
import textacy
# Requires a spaCy model to be loaded separately
import spacy
nlp = spacy.load('en_core_web_sm')
doc = nlp('Your text here')
extracted = textacy.extract.ngrams(doc, n=2)Verify before relying
- Specific spaCy version compatibility requirements beyond what the fact sheet states.
- Performance characteristics when processing large document collections.
- Whether all features remain functional given the dormant maintenance status.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 14 packagescachetoolscataloguecytoolzfloretjellyfishjoblibnetworkxnumpypyphenrequestsscipyscikit-learnspacytqdm |
| Maintenance | Dormant 1,230 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 102,787 / month, #12,847 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseNatural Language :: EnglishProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.9Topic :: Text Processing :: Linguistic |
Evidence: textacy-0.13.0-py3-none-any.whl
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